1. Field
Apparatuses and methods consistent with exemplary embodiment relate to an apparatus and method for estimating noise of an image signal.
2. Description of the Related Art
Numerous methods for noise processing have been developed so far. In particular, for an image signal presented in a device which expresses a video image, such as a television, if the image signal has much noise and thus its display quality is significantly degraded, the display quality may be remarkably improved by processing the noise. Representative noise canceling methods may include a two-dimensional (2D) noise canceling method as a spatial processing method, a three-dimensional (3D) noise canceling method as a tempo-spatial noise canceling method, and so forth.
The aforementioned noise canceling methods show excellent performance in light of noise cancellation for an image having much noise. However, they show poor performance in terms of noise cancellation and at the same time, protection of an image component, for a broadcast image having a little noise.
This is because the conventional methods process a noise dispersion value, which is a criterion for determining noise, as a constant value, regardless of a region, assuming that noise is a component independent of a signal. However, in practice, in an image signal, the amplitude of noise varies from region to region. For some regions, leaving noise, which does not change temporally, in an image may result in subjectively better display quality in a sense that texture is preserved.
FIG. 1 is a diagram of a general noise estimation block.
Referring to FIG. 1, an image receiver 110 receives an image signal and outputs the image signal to a frame buffer 120.
The frame buffer 120 buffers the input image signal in predetermined units, and outputs the image signal after a predetermined time.
A noise estimator 140 receives the image signal output from the frame buffer 120 and an image signal which temporally continues from the image signal, and calculates a dispersion value of noise values after a noise value over a predetermined value is canceled, out of noise values generated due to the time.
In noise calculation, the noise estimator 140 obtains an average of differences between the image and its neighboring images, and estimates a representative noise dispersion value for all the regions.
The noise canceller 150 cancels noise from the input image signal by referring to the estimated noise dispersion value.
The conventional methods show poor performance in a broadcast image having weak noise because of processing the noise dispersion value as a constant value regardless of a region.
The noise left in the image does not negatively affect the display quality or resolution of the reproduced image signal when it is displayed on a small-screen display. However, when such noise is displayed on a large-screen display, the noise is displayed after being enlarged, thus negatively affecting the display quality or resolution of the reproduced image signal. To solve the display quality degradation problem, noise processing is required.